A fundamental but unsolved question in neuroscience is how specific connections between brain cells (neurons) underlie information processing. Circuits in the cerebral cortex?the part of the mammalian brain that underlies high-level sensory, motor, and cognitive function?consists of tens of thousands of neurons, each of which sends and receives thousands of connections. Perhaps the biggest reason we don't understand the cerebral cortex is that we don't have an actual wiring diagram of any single cortical circuit. But even if we had a wiring diagram, we would need to know what each neuron in a circuit is doing: its physiology. In this proposal, we plan study the functional logic of networks in the visual cortex by examining groups of connected neurons whose responses to visual stimuli have been characterized. We will combine two techniques to tackle this difficult problem. Connections between neurons will be determined with a modified virus that allows us to specifically labels ensembles of neurons, all of which connect with a single 'target' neuron in each experiment. Once the neurons are labeled, we will use an advanced form of scanning-laser imaging (calcium imaging with two-photon microscopy) that allows us to make movies of each neuron's activity in response to carefully chosen visual stimuli. Together, these tools will allow to probe the functional logic of cortical circuits: the relationship between neuronal function and the wiring between neurons. The cerebral cortex is a network of networks. There are many different cortical regions each of which has its distinct inputs and outputs and distinct physiological properties. For instance, roughly ten visual cortical areas process different aspects of visual stimuli. We will start by studying the functional logic of wiring within three visual cortical areas: V1, AL and PM. We will then examine the functional logic of connections between these areas. The viral strategy that we employ is currently the only method that allow for both local and inter- areal connection to be studied along with physiology. The data we collect will help us understand feedforward, lateral, and feedback connections in cortical circuits and will form the foundation of new, data-driven models of cortical function.